DTSC 3000: Special Topics in Data Science: History and Philosophy of Computing
University of North Carolina, Charlotte
Special topics in interdisciplinary data science.� Topic varies by semester and instructor. Section information text: Students will gain the tools to explore and understand the developments of computing technology in multiple societies and relating to many lines of philosophical and social scientific inquiry, while also working through their own perspectives as students, citizens, and members of the world community. This course is structured around a series of readings, lectures, and in-person and online discussions fueled by question-and-answer assignments, and various other assignments to help students engage with the perspectives of the material and each other.
Average GPA: 3.41
Grade distribution records: 88 students across 6 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A | 49 | 55.7% |
| B | 21 | 23.9% |
| C | 6 | 6.8% |
| D | 2 | 2.3% |
| F | 2 | 2.3% |
| W | 6 | 6.8% |
Based on 88 student grade records across 6 terms and 5 professors.
Instructors
- Marco Scipioni 51 students, Average GPA 3.52
- Damien Williams 13 students, Average GPA 3.00
- Jeffrey Barto 10 students, Average GPA 3.33
- Felecia Harris 9 students, Average GPA 3.44
- Bienvenido Rodriguez-Medina 5 students, Average GPA 3.40